# Ethics Sheets for AI Tasks

arXiv: https://arxiv.org/abs/2107.01183 · HTML: https://mlsanity.com/paper/2107.01183/

## Key facts

- Cited by 18 papers in the map (data through 14 Oct 2026).
- Builds on 7 of its 48 references that are in the map.
- First posted on arXiv 2 Jul 2021.

## Builds on (most cited first, 7 of 7)

- [Datasheets for Datasets](https://mlsanity.com/paper/1803.09010/) (2018)
- [Model Cards for Model Reporting](https://mlsanity.com/paper/1810.03993/) (2018)
- [Green AI](https://mlsanity.com/paper/1907.10597/) (2019)
- [Examining Gender and Race Bias in Two Hundred Sentiment Analysis Systems](https://mlsanity.com/paper/1805.04508/) (2018)
- [Assessing Gender Bias in Machine Translation -- A Case Study with Google Translate](https://mlsanity.com/paper/1809.02208/) (2018)
- [Analyzing the Behavior of Visual Question Answering Models](https://mlsanity.com/paper/1606.07356/) (2016)
- [Debiasing Skin Lesion Datasets and Models? Not So Fast](https://mlsanity.com/paper/2004.11457/) (2020)

## Built on by (most cited first, 18 of 18)

- [On Measures of Biases and Harms in NLP](https://mlsanity.com/paper/2108.03362/) (2021)
- [Assessing Language Model Deployment with Risk Cards](https://mlsanity.com/paper/2303.18190/) (2023)
- [Best Practices in the Creation and Use of Emotion Lexicons](https://mlsanity.com/paper/2210.07206/) (2022)
- [Ethics Sheet for Automatic Emotion Recognition and Sentiment Analysis](https://mlsanity.com/paper/2109.08256/) (2021)
- [Reward Reports for Reinforcement Learning](https://mlsanity.com/paper/2204.10817/) (2022)
- [Enabling Classifiers to Make Judgements Explicitly Aligned with Human Values](https://mlsanity.com/paper/2210.07652/) (2022)
- [Forgotten Knowledge: Examining the Citational Amnesia in NLP](https://mlsanity.com/paper/2305.18554/) (2023)
- [We Should Evaluate Real-World Impact](https://mlsanity.com/paper/2507.05973/) (2025)
- [Experimental Standards for Deep Learning in Natural Language Processing Research](https://mlsanity.com/paper/2204.06251/) (2022)
- [BLIP: Facilitating the Exploration of Undesirable Consequences of Digital Technologies](https://mlsanity.com/paper/2405.06783/) (2024)
- [Steering LLMs for Culturally Localized Generation](https://mlsanity.com/paper/2603.23301/) (2026)
- [Thorny Roses: Investigating the Dual Use Dilemma in Natural Language Processing](https://mlsanity.com/paper/2304.08315/) (2023)
- [Grasping AI: experiential exercises for designers](https://mlsanity.com/paper/2310.01282/) (2023)
- [Promoting the Responsible Development of Speech Datasets for Mental Health and Neurological Disorders Research](https://mlsanity.com/paper/2406.04116/) (2024)
- [Just Because We Camp, Doesn't Mean We Should: The Ethics of Modelling Queer Voices](https://mlsanity.com/paper/2406.07504/) (2024)
- [Understanding Gender Bias in AI-Generated Product Descriptions](https://mlsanity.com/paper/2506.05390/) (2025)
- [Ethics Whitepaper: Whitepaper on Ethical Research into Large Language Models](https://mlsanity.com/paper/2410.19812/) (2024)
- [Affect as a proxy for literary mood](https://mlsanity.com/paper/2304.02894/) (2023)

## Abstract (arXiv)

Several high-profile events, such as the mass testing of emotion recognition systems on vulnerable sub-populations and using question answering systems to make moral judgments, have highlighted how technology will often lead to more adverse outcomes for those that are already marginalized. At issue here are not just individual systems and datasets, but also the AI tasks themselves. In this position paper, I make a case for thinking about ethical considerations not just at the level of individual models and datasets, but also at the level of AI tasks. I will present a new form of such an effort, Ethics Sheets for AI Tasks, dedicated to fleshing out the assumptions and ethical considerations hidden in how a task is commonly framed and in the choices we make regarding the data, method, and evaluation. I will also present a template for ethics sheets with 50 ethical considerations, using the task of emotion recognition as a running example. Ethics sheets are a mechanism to engage with and document ethical considerations before building datasets and systems. Similar to survey articles, a small number of ethics sheets can serve numerous researchers and developers.